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Artificial Intelligence and National Security
Updated August 26, 2020
Congressional Research Service
https://crsreports.congress.gov
R45178
Artificial Intelligence and National Security
Summary
Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant
implications for national security. As such, the U.S. Department of Defense (DOD) and other
nations are developing AI applications for a range of military functions. AI research is underway
in the fields of intelligence collection and analysis, logistics, cyber operations, information
operations, command and control, and in a variety of semiautonomous and autonomous vehicles.
Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action
has the potential to shape the technology’s development further, with budgetary and legislative
decisions influencing the growth of military applications as well as the pace of their adoption.
AI technologies present unique challenges for military integration, particularly because the bulk
of AI development is happening in the commercial sector. Although AI is not unique in this
regard, the defense acquisition process may need to be adapted for acquiring emerging
technologies like AI. In addition, many commercial AI applications must undergo significant
modification prior to being functional for the military. A number of cultural issues also challenge
AI acquisition, as some commercial AI companies are averse to partnering with DOD due to
ethical concerns, and even within the department, there can be resistance to incorporating AI
technology into existing weapons systems and processes.
Potential international rivals in the AI market are creating pressure for the United States to
compete for innovative military AI applications. China is a leading competitor in this regard,
releasing a plan in 2017 to capture the global lead in AI development by 2030. Currently, China is
primarily focused on using AI to make faster and more well-informed decisions, as well as on
developing a variety of autonomous military vehicles. Russia is also active in military AI
development, with a primary focus on robotics.
Although AI has the potential to impart a number of advantages in the military context, it may
also introduce distinct challenges. AI technology could, for example, facilitate autonomous
operations, lead to more informed military decisionmaking, and increase the speed and scale of
military action. However, it may also be unpredictable or vulnerable to unique forms of
manipulation. As a result of these factors, analysts hold a broad range of opinions on how
influential AI will be in future combat operations. While a small number of analysts believe that
the technology will have minimal impact, most believe that AI will have at least an
evolutionary—if not revolutionary—effect.
Military AI development presents a number of potential issues for Congress:
What is the right balance of commercial and government funding for AI
development?
How might Congress influence defense acquisition reform initiatives that
facilitate military AI development?
What changes, if any, are necessary in Congress and DOD to implement effective
oversight of AI development?
How should the United States balance research and development related to
artificial intelligence and autonomous systems with ethical considerations?
What legislative or regulatory changes are necessary for the integration of
military AI applications?
What measures can Congress take to help manage the AI competition globally?
Congressional Research Service
Artificial Intelligence and National Security
Contents
Introduction ..................................................................................................................................... 1
AI Terminology and Background .................................................................................................... 1
Issues for Congress .......................................................................................................................... 5
AI Applications for Defense ............................................................................................................ 9
Intelligence, Surveillance, and Reconnaissance ...................................................................... 10
Logistics .................................................................................................................................. 10
Cyberspace Operations............................................................................................................. 11
Information Operations and “Deep Fakes” .............................................................................. 11
Command and Control ............................................................................................................ 12
Semiautonomous and Autonomous Vehicles .......................................................................... 13
Lethal Autonomous Weapon Systems (LAWS) ...................................................................... 14
Military AI Integration Challenges ................................................................................................ 15
Technology .............................................................................................................................. 16
Process .................................................................................................................................... 16
Personnel ................................................................................................................................. 18
Culture ..................................................................................................................................... 19
International Competitors .............................................................................................................. 20
China ....................................................................................................................................... 20
Russia ...................................................................................................................................... 24
International Institutions................................................................................................................ 26
AI Opportunities and Challenges .................................................................................................. 27
Autonomy................................................................................................................................ 27
Speed and Endurance .............................................................................................................. 28
Scaling ..................................................................................................................................... 28
Information Superiority ........................................................................................................... 29
Predictability ........................................................................................................................... 29
Explainability .......................................................................................................................... 32
Exploitation ............................................................................................................................. 34
AI’s Potential Impact on Combat .................................................................................................. 35
Minimal Impact on Combat .................................................................................................... 35
Evolutionary Impact on Combat ............................................................................................. 36
Revolutionary Impact on Combat ........................................................................................... 37
Figures
Figure 1. Relationships of Selected AI Definitions ......................................................................... 4
Figure 2. Chinese Investment in U.S. AI Companies, 2010-2017 ................................................. 22
Figure 3. Value of Autonomy to DOD Missions ........................................................................... 28
Figure 4. AI and Image Classifying Errors .................................................................................... 30
Figure 5. AI and Context ............................................................................................................... 31
Figure 6. Adversarial Images ......................................................................................................... 34
Congressional Research Service
Artificial Intelligence and National Security Tables Table 1. Taxonomy of Historical AI Definitions ............................................................................. 3 Contacts Author Information........................................................................................................................ 39 Acknowledgments ......................................................................................................................... 39 Congressional Research Service
Artificial Intelligence and National Security
Introduction1
Artificial intelligence (AI) is a rapidly growing field of technology that is capturing the attention
of commercial investors, defense intellectuals, policymakers, and international competitors alike,
as evidenced by a number of recent initiatives. On July 20, 2017, the Chinese government
released a strategy detailing its plan to take the lead in AI by 2030. Less than two months later
Vladimir Putin publicly announced Russia’s intent to pursue AI technologies, stating, “[W]hoever
becomes the leader in this field will rule the world.”2 Similarly, the U.S. National Defense
Strategy, released in January 2018, identified artificial intelligence as one of the key technologies
that will “ensure [the United States] will be able to fight and win the wars of the future.”3
The U.S. military is already integrating AI systems into combat via a spearhead initiative called
Project Maven, which uses AI algorithms to identify insurgent targets in Iraq and Syria.4 These
dynamics raise several questions that Congress addressed in hearings during 2017, 2018, and
2019: What types of military AI applications are possible, and what limits, if any, should be
imposed? What unique advantages and vulnerabilities come with employing AI for defense? How
will AI change warfare, and what influence will it have on the military balance with U.S.
competitors? Congress has a number of oversight, budgetary, and legislative tools available that it
may use to influence the answers to these questions and shape the future development of AI
technology.
AI Terminology and Background5
Almost all academic studies in artificial intelligence acknowledge that no commonly accepted
definition of AI exists, in part because of the diverse approaches to research in the field.
Likewise, although Section 238 of the FY2019 National Defense Authorization Act (NDAA)
directs the Secretary of Defense to produce a definition of artificial intelligence by August 13,
2019, no official U.S. government definition of AI yet exists.6 The FY2019 NDAA does,
however, provide a definition of AI for the purposes of Section 238:
1. Any artificial system that performs tasks under varying and unpredictable
circumstances without significant human oversight, or that can learn from
experience and improve performance when exposed to data sets.
2. An artificial system developed in computer software, physical hardware, or other
context that solves tasks requiring human-like perception, cognition, planning,
learning, communication, or physical action.
1 This report was originally written by Daniel S. Hoadley, U.S. Air Force Fellow. It has been updated by Kelley M.
Sayler, Analyst in Advanced Technology and Global Security.
2 China State Council, “A Next Generation Artificial Intelligence Development Plan,” July 20, 2017, translated by New
America, https://www.newamerica.org/documents/1959/translation-fulltext-8.1.17.pdf, and Tom Simonite, “For
Superpowers, Artificial Intelligence Fuels New Global Arms Race,” Wired, August 8, 2017, https://www.wired.com/
story/for-superpowers-artificial-intelligence-fuels-new-global-arms-race.
3 Department of Defense, Summary of the 2018 National Defense Strategy, p.3, https://dod.defense.gov/Portals/1/
Documents/pubs/2018-National-Defense-Strategy-Summary.pdf.
4 Marcus Weisgerber, “The Pentagon’s New Algorithmic Warfare Cell Gets Its First Mission: Hunt ISIS,” Defense
One, May 14, 2017, http://www.defenseone.com/technology/2017/05/pentagons-new-algorithmic-warfare-cell-gets-its-
first-mission-hunt-isis/137833/.
5 For a general overview of AI, see CRS In Focus IF10608, Overview of Artificial Intelligence, by Laurie A. Harris.
6 P.L. 115-232, Section 2, Division A, Title II, §238.
Congressional Research Service 1Artificial Intelligence and National Security
3. An artificial system designed to think or act like a human, including cognitive
architectures and neural networks.
4. A set of techniques, including machine learning that is designed to approximate a
cognitive task.
5. An artificial system designed to act rationally, including an intelligent software
agent or embodied robot that achieves goals using perception, planning,
reasoning, learning, communicating, decision-making, and acting.7
This definition encompasses many of the descriptions in Table 1 below, which summarizes
various AI definitions in academic literature.
The field of AI research began in the 1940s, but an explosion of interest in AI began around 2010
due to the convergence of three enabling developments: (1) the availability of “big data” sources,
(2) improvements to machine learning approaches, and (3) increases in computer processing
power.8 This growth has advanced the state of Narrow AI, which refers to algorithms that address
specific problem sets like game playing, image recognition, and navigation. All current AI
systems fall into the Narrow AI category. The most prevalent approach to Narrow AI is machine
learning, which involves statistical algorithms that replicate human cognitive tasks by deriving
their own procedures through analysis of large training data sets. During the training process, the
computer system creates its own statistical model to accomplish the specified task in situations it
has not previously encountered.
Experts generally agree that it will be many decades before the field advances to develop General
AI, which refers to systems capable of human-level intelligence across a broad range of tasks.9
Nevertheless, the rapid advancements in Narrow AI have sparked a wave of investment, with U.S.
venture capitalists investing an estimated $8 billion in AI research in 2018 alone.10 Similarly,
DOD’s unclassified investments in AI have grown from just over $600 million in FY2016 to $2.5
billion in FY2021 (including investments in autonomy), with the Department reportedly
maintaining over 600 active AI projects.11
AI has a number of unique characteristics that may be important to consider as these technologies
enter the national security arena. First, AI has the potential to be integrated across a variety of
applications, improving the so-called “Internet of Things” in which disparate devices are
networked together to optimize performance.12 As Kevin Kelley, the founder of Wired magazine,
7 Ibid. For a critique of this definition, see Defense Innovation Board (DIB), “AI Principles: Recommendations on the
Ethical Use of Artificial Intelligence by the Department of Defense – Supporting Document,” November 2019, pp. 8-
10, https://media.defense.gov/2019/Oct/31/2002204459/-1/-1/0/
DIB_AI_PRINCIPLES_SUPPORTING_DOCUMENT.PDF. The DIB instead defines artificial intelligence as “a
variety of information processing techniques and technologies used to perform a goal-oriented task and the means to
reason in pursuit of that task.”
8 Executive Office of the President, National Science and Technology Council, Committee on Technology, Preparing
for the Future of Artificial Intelligence, October 12, 2016, p. 6, https://obamawhitehouse.archives.gov/sites/default/
files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf.
9 Ibid., pp. 7-9.
10 Deloitte, “Future in the balance? How countries are pursuing an AI advantage,” https://www2.deloitte.com/us/en/
insights/focus/cognitive-technologies/ai-investment-by-country.html.
11 See Govini, Department of Defense Artificial Intelligence, Big Data, and Cloud Taxonomy, December 3, 2017, p. 9;
Office of the Under Secretary of Defense (Comptroller)/Chief Financial Officer, Defense Budget Overview: United
States Department of Defense FY2021 Budget Request, February 2020, p. 1-9; and Brendan McCord, Eye on AI,
August 28, 2019, transcript available at https://static1.squarespace.com/static/5b75ac0285ede1b470f58ae2/t/
5d6aa8edb91b0c0001c7a05f/1567.
12 See Steve Ranger, “What is the IoT? Everything you need to know about the Internet of Things right now,”
Congressional Research Service 2Artificial Intelligence and National Security
states, “[AI] will enliven inert objects, much as electricity did more than a century ago.
Everything that we formerly electrified we will now cognitize.”13 Second, many AI applications
are dual-use, meaning they have both military and civil applications. For example, image
recognition algorithms can be trained to recognize cats in YouTube videos as well as terrorist
activity in full motion video captured by uninhabited aerial vehicles over Syria or Afghanistan.14
Third, AI is a relatively transparent enabling capability, meaning that its integration into a product
may not be immediately recognizable. By and large, AI procurement will not result in countable
objects. Rather, the algorithm will be purchased separately and incorporated into a larger system.
As an expert in the field points out, “We will not buy AI. It will be used to solve problems, and
there will be an expectation that AI will be infused in most things we do.”15
AI Concepts
Table 1. Taxonomy of Historical AI Definitions
Systems That Think Like Humans Systems That Think Rationally
“The automation of activities that we associate with “The study of computations that make possible to
human thinking, activities such as decision making, perceive, reason, and act.”
problem solving, and learning.”
—Winston, 1992
—Bellman, 1978
Systems That Act Like Humans Systems That Act Rationally
“The art of creating machines that perform functions “The branch of computer science that is concerned
that require intelligence when performed by people.” with the automation of intelligent behavior.”
—Kurzweil, 1990 —Luger and Stubblefield, 1993
Selected Definitions—Where possible, an official U.S. government document is cited.
Automated systems. “A physical system that functions with no (or limited) human operator involvement,
typically in structured and unchanging environments, and the system’s performance is limited to the specific
set of actions that it has been designed to accomplish ... typically these are well-defined tasks that have
predetermined responses according to simple scripted or rule-based prescriptions.”16
Autonomy. “The condition or quality of being self-governing in order to achieve an assigned task based on
the system’s own situational awareness (integrated sensing, perceiving, and analyzing), planning, and decision
making.”17
Autonomous Weapon System (aka Lethal Autonomous Weapon System, LAWS). “A weapon system
that, once activated, can select and engage targets without further intervention by a human operator.”18
ZDNet.com, August 21, 2018, https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-
know-about-the-iot-right-now/.
13 Kevin Kelly, “The Three Breakthroughs That Have Finally Unleashed AI on the World,” Wired, October 27, 2014,
https://www.wired.com/2014/10/future-of-artificial-intelligence.
14
Greg Allen and Taniel Chan, Artificial Intelligence and National Security, Belfer Center for Science and
International Affairs, July 2017, p. 47.
15 Steve Mills, Presentation at the Global Security Forum, Center for Strategic and International Studies, Washington,
DC, November 7, 2017.
16 Andrew Ilachinski, AI, Robots, and Swarms: Issues, Questions, and Recommended Studies, Center for Naval
Analysis, January 2017, p. 6.
17 Department of Defense, Joint Concept for Robotic and Autonomous Systems, October 19, 2016, p. A-3.
18 Department of Defense, Directive 3000.09, Autonomy in Weapon Systems, http://www.esd.whs.mil/Portals/54/
Documents/DD/issuances/DODd/300009p.pdf.
Congressional Research Service 3Artificial Intelligence and National Security
Human-Supervised Autonomous Weapon System. “An autonomous weapon system that is designed to
provide human operators with the ability to intervene and terminate engagements, including in the event
of a weapon system failure, before unacceptable levels of damage occur.”19
Semi-Autonomous Weapon System. “A weapon system that, once activated, is intended to only engage
individual targets or specific target groups that have been selected by a human operator.”20
Robot. “A powered machine capable of executing a set of actions by direct human control, computer
control, or a combination of both. At a minimum it is comprised of a platform, software, and a power
source.”21
Understanding the relationships between these terms can be challenging, as they may be used interchangeably in
the literature and definitions often conflict with one another. For example, some studies delineate between
automated systems and autonomous systems based on the system’s complexity, arguing that automated systems
are strictly rule-based, while autonomous systems exhibit artificial intelligence. Some, including the Department of
Defense, categorize autonomous weapon systems based not on the system’s complexity, but rather on the type of
function being executed without human intervention (e.g., target selection and engagement).22 Still others describe
AI as a means of automating cognitive tasks, with robotics automating physical tasks. This framework, however,
may not be sufficient to describe how AI systems function, as such systems do not merely replicate human
cognitive functions and often produce unanticipated outputs. In addition, a robot may be automated or
autonomous and may or may not contain an AI algorithm. Figure 1 illustrates these relationships, based on the
above selected definitions of each term.
Figure 1. Relationships of Selected AI Definitions
Source: CRS.
19 Ibid.
20 Ibid.
21 Department of Defense, Joint Concept for Robotic and Autonomous Systems, p. A-3.
22 See Paul Scharre and Michael C. Horowitz, An Introduction to Autonomy in Weapon Systems, Center for a New
American Security, February 2015, pp. 6-7.
Congressional Research Service 4Artificial Intelligence and National Security
Issues for Congress
A number of Members of Congress have called for action on military AI. During the opening
comments to a January 2018 hearing before the House Armed Services Subcommittee on
Emerging Threats, the subcommittee chair called for a “national level effort” to preserve a
technological edge in the field of AI.23 Former Deputy Secretary of Defense Robert Work argued
in a November 2017 interview that the federal government needs to address AI issues at the
highest levels, further stating that “this is not something the Pentagon can fix by itself.”24 Other
analysts have called for a national AI strategy to articulate AI objectives and drive whole-of-
government initiatives and cross-cutting investments.25
In the meantime, DOD has published a classified AI strategy and is carrying out multiple tasks
directed by DOD guidance and the FY2019 NDAA, including
establishing a Joint Artificial Intelligence Center (JAIC), which now
“coordinate[s] the efforts of the Department to develop, mature, and transition
artificial intelligence technologies into operational use”;26
publishing a strategic roadmap for AI development and fielding, as well as
guidance on “appropriate ethical, legal, and other policies for the Department
governing the development and use of artificial intelligence enabled systems and
technologies in operational situations”;27 and
establishing a National Security Commission on Artificial Intelligence to conduct
a comprehensive assessment of militarily relevant AI technologies and provide
recommendations for strengthening U.S. competitiveness.28
23 U.S. Congress, House of Representatives Committee on Armed Services, Subcommittee on Emerging Threats and
Capabilities, Hearing on China’s Pursuit of Emerging Technologies, 115th Cong., 2nd sess., January 9, 2018, transcript
available at http://www.cq.com/doc/congressionaltranscripts-5244793?1; remarks by Rep. Joe Wilson.
24 Colin Clark, “Our Artificial Intelligence ‘Sputnik Moment’ is Now: Eric Schmidt and Bob Work,” Breaking
Defense, November 1, 2017, https://breakingdefense.com/2017/11/our-artificial-intelligence-sputnik-moment-is-now-
eric-schmidt-bob-work/.
25 Jack Corrigan, “U.S. Needs a National Strategy for Artificial Intelligence, Lawmakers and Experts Say,” Defense
One, July 14, 2018, https://www.defenseone.com/technology/2018/07/us-needs-national-strategy-artificial-intelligence-
lawmakers-and-experts-say/149644/.
26 Sydney J. Freedberg, Jr., “Pentagon Rolls Out Major Cyber, AI Strategies This Summer,” Breaking Defense, July 17,
2018, https://breakingdefense.com/2018/07/pentagon-rolls-out-major-cyber-ai-strategies-this-summer/; and P.L. 115-
232, Section 2, Division A, Title X, §1051.
27 P.L. 115-232, Section 2, Division A, Title II, §238. In support of this mandate, the Defense Innovation Board, an
independent federal advisory committee to the Secretary of Defense, has drafted recommendations for the ethical use of
artificial intelligence. See Defense Innovation Board, “AI Principles: Recommendations on the Ethical Use of Artificial
Intelligence by the Department of Defense,” October 31, 2019, https://media.defense.gov/2019/Oct/31/2002204458/-1/-
1/0/DIB_AI_PRINCIPLES_PRIMARY_DOCUMENT.PDF.
28
Ibid. and P.L. 115-232, Section 2, Division A, Title X, §1051. The Commission’s Interim Report, which assesses the
challenges and opportunities of militarily relevant AI technologies, is available at https://drive.google.com/file/d/
153OrxnuGEjsUvlxWsFYauslwNeCEkvUb/view. It identifies five key lines of effort for U.S. AI competitiveness: (1)
investing in research and development, (2) applying AI to national security missions, (3) training and recruiting AI
talent, (4) protecting and building upon U.S. technology advantages, and (5) marshalling global AI cooperation. The
commission is releasing recommendations for implementing these lines of effort every quarter. Its first quarter
recommendations, released in March 2020, are available at
https://drive.google.com/file/d/1wkPh8Gb5drBrKBg6OhGu5oNaTEERbKss/view. Second quarter recommendations,
released in July 2020, are available at
https://drive.google.com/file/d/1LDrd6T7H50ry9uXNA6cwhsrtnpQ63EWH/view.
Congressional Research Service 5Artificial Intelligence and National Security These initiatives will present a number of oversight opportunities for Congress. In addition, Congress may consider the adequacy of current DOD funding levels for AI. Lieutenant General John Shanahan, the former director of the JAIC, identified funding as a barrier to future progress.29 Although DOD funding for AI has increased, beginning in 2018—to include the JAIC’s $1.75 billion six-year budget and the Defense Advanced Research Projects Agency’s (DARPA’s) $2 billion multiyear investment in over 20 AI programs—some experts have argued that additional DOD funding will be required to keep pace with U.S. competitors and avoid an “innovation deficit” in military technology.30 Critics of increased federal funding contend that significant increases to appropriations may not be required, as the military should be leveraging research and development (R&D) conducted in the commercial sector. The 2017 National Security Strategy identifies a need to “establish strategic partnerships to align private sector R&D resources to priority national security applications” and to reward government agencies that “take risks and rapidly field emerging commercial technologies.”31 In addition, the Office of Management and Budget directed DOD in preparing its FY2020 budget to “seek to rapidly field innovative technologies from the private sector, where possible, that are easily adaptable to Federal needs, rather than reinventing solutions in parallel.”32 Some experts in the national security community also argue that it would not be a responsible use of taxpayer money to duplicate efforts devoted to AI R&D in the commercial sector when companies take products 90% of the way to a useable military application.33 Others contend that a number of barriers stand in the way of transitioning AI commercial technology to DOD, and that reforming aspects of the defense acquisition process may be necessary.34 These issues are discussed in more detail later in this report.35 One impediment to accurately evaluating funding levels for AI is the lack of a stand-alone AI Program Element (PE) in DOD funding tables. As a result, AI R&D appropriations are spread throughout generally titled PEs and incorporated into funding for larger systems with AI components. For example, in the FY2019 National Defense Authorization Act, AI funding is spread throughout the PEs for the High Performance Computing Modernization Program and 29 Justin Doubleday, “Project Maven Aims to Introduce AI tools into Services’ Intel Systems,” Inside Defense, January 5, 2018, https://insidedefense.com/inside-army/project-maven-aims-introduce-ai-tools-services-intel-systems, and Jason Sherman, “ASB: S&T Funding Inadequate to Support ‘Big Bets’ on Disruptive Technologies,” Inside Defense, December 15, 2017, https://insidedefense.com/inside-army/asb-st-funding-inadequate-support-big-bets-disruptive- technologies. 30 “DARPA Announces $2 Billion Campaign to Develop Next Wave of AI Technologies,” DARPA, September 7, 2018, https://www.darpa.mil/news-events/2018-09-07; and Elsa B. Kania, “Battlefield Singularity: Artificial Intelligence, Military Revolution, and China’s Future Military Power,” Center for a New American Security, November 28, 2017, pp. 40-41, https://s3.amazonaws.com/files.cnas.org/documents/Battlefield-Singularity-November- 2017.pdf?mtime=20171129235804. 31 The White House, National Security Strategy of the United States of America, December 2017, p. 21, https://www.whitehouse.gov/wp-content/uploads/2017/12/NSS-Final-12-18-2017-0905-2.pdf. 32 Executive Office of the President, Director, Office of Management and Budget, Memorandum for the Heads of Executive Departments and Agencies, “FY 2020 Administration Research and Development Budget Priorities,” July 31, 2018, https://www.whitehouse.gov/wp-content/uploads/2018/07/M-18-22.pdf. 33 Dr. Matthijs Broer, Chief Technology Officer, Central Intelligence Agency, Comments at Defense One Summit, November 9, 2017. 34 Testimony of Paul Scharre, House Armed Services Committee, Subcommittee on Emerging Threats and Capabilities, Hearing on China’s Pursuit of Emerging Technologies. 35 For a discussion of recent defense acquisitions reform initiatives, see CRS Report R45068, Acquisition Reform in the FY2016-FY2018 National Defense Authorization Acts (NDAAs), by Moshe Schwartz and Heidi M. Peters. Congressional Research Service 6
Artificial Intelligence and National Security Dominant Information Sciences and Methods, among others.36 On the other hand, a dedicated PE for AI may lead to a false precision, as it may be challenging to identify exact investments in enabling technologies like AI. The lack of an official U.S. government definition of AI could further complicate such an assessment. Congress may also consider specific policies for the development and use of military AI applications. Many experts fear that the pace of AI technology development is moving faster than the speed of policy implementation. Former Chairman of the House Armed Services Committee Representative Mac Thornberry has echoed this sentiment, stating, “It seems to me that we’re always a lot better at developing technologies than we are the policies on how to use them.”37 Congress may assess the need for new policies or modifications to existing laws to account for AI developments and ensure that AI applications are free from bias.38 Perhaps the most immediate policy concern among AI analysts is the absence of an independent entity to develop and enforce AI safety standards and to oversee government-wide AI research.39 Former Secretary of Defense Ashton B. Carter, for example, has suggested the need for an “AI czar” to coordinate such efforts.40 Relatedly, Congress may consider debating policy options on the development and fielding of Lethal Autonomous Weapons Systems (LAWS), which may use AI to select and engage targets. Since 2014, the United States has participated in international discussions of LAWS at the United Nations (U.N.) Convention on Certain Conventional Weapons (CCW). Approximately 30 state parties have called for a treaty banning “fully autonomous weapon systems” due to ethical considerations, while others have called for formal regulations or political declarations.41 Some analysts are concerned that efforts to ban or regulate LAWS could impose strict controls on AI applications that could be adapted for lethal use, thereby stifling development of other useful military—or even commercial—technology. During recent testimony to the U.N., one expert stated, “If we agree to foreswear some technology, we could end up giving up some uses of automation that could make war more humane. On the other hand a headlong rush into a future of increasing autonomy with no discussion of where it is taking us, is not in humanity’s interest either.” He suggested the leading question for considering military AI applications ought to be, “What role do we want humans to play in wartime decision making?”42 36 P.L. 115-232, Section 2, Division D, Title XLIII, §4301. 37 Morgan Chalfant, “Congress Told to Brace for Robotic Soldiers,” The Hill, March 1, 2017, http://thehill.com/policy/ cybersecurity/321825-congress-told-to-brace-for-robotic-soldiers. 38 See Parmy Olson, “Racist, Sexist AI Could Be a Bigger Problem than Lost Jobs,” Forbes, February 26, 2018, https://www.forbes.com/sites/parmyolson/2018/02/26/artificial-intelligence-ai-bias-google/#3326a1951a01. 39 CRS discussion with Mike Garris, National Institute of Standards and Technology, Co-Chairman, Subcommittee on Machine Learning and Artificial Intelligence, Committee on Technology, National Science and Technology Council, October 2, 2017. 40 David Ignatius, “China’s application of AI should be a Sputnik moment for the U.S. But will it be?,” New York Times, November 6, 2018, https://www.washingtonpost.com/opinions/chinas-application-of-ai-should-be-a-sputnik- moment-for-the-us-but-will-it-be/2018/11/06/69132de4-e204-11e8-b759-3d88a5ce9e19_story.html?utm_term= .88a808915d9c. 41 See “Country Views on Killer Robots,” Campaign to Stop Killer Robots, April 13, 2018, https://www.stopkillerrobots.org/wp-content/uploads/2018/04/KRC_CountryViews_13Apr2018.pdf; and U.N. CCW Working Papers and Statements at https://www.unog.ch/__80256ee600585943.nsf/(httpPages)/ 7c335e71dfcb29d1c1258243003e8724?OpenDocument&ExpandSection=3#_Section3. 42 Paul Scharre, Remarks to the United Nations, Group of Governmental Experts on Lethal Autonomous Weapons Systems, November 15, 2017, Geneva, Switzerland, https://s3.amazonaws.com/files.cnas.org/documents/Scharre- Remarks-to-UN-on-Autonomous-Weapons-15-Nov-2017.pdf?mtime=20171120095806. For more information on Congressional Research Service 7
Artificial Intelligence and National Security Congress may consider the growth of international competition in the AI market and the danger of foreign exploitation of U.S. AI technology for military purposes. In particular, the Chinese government is reported to be aggressively pursuing AI investments in the United States. Amid growing scrutiny of transactions involving Chinese firms in the semiconductor industry, in September 2017 President Trump, following the recommendation of the Committee on Foreign Investment in the United States (CFIUS), blocked a Chinese firm from acquiring Lattice Semiconductor, a U.S. company that manufactures chips that are a critical design element for AI technology.43 In this way, some experts believe that CFIUS may provide a means of protecting strategically significant technologies like AI.44 Indeed, the Foreign Investment Risk Review Modernization Act of 2018 (FIRRMA) expands CFIUS’s ability to review certain foreign investments, including those involving “emerging and foundational technologies.” It also authorized CFIUS to consider “whether a covered transaction involves a country of special concern that has a demonstrated or declared strategic goal of acquiring a type of critical technology or critical infrastructure that would affect United States leadership in areas related to national security.”45 Congress may monitor the implementation of FIRRMA and assess whether additional reforms might be necessary to maintain effective congressional oversight of sensitive transactions. In addition, many analysts believe that it may be necessary to reform federal data policies associated with AI. Large data pools serve as the training sets needed for building many AI systems, and government data may be particularly important in developing military AI applications. However, some analysts have observed that much of this data is classified, access- controlled, or otherwise protected on privacy grounds. These analysts contend that Congress should implement a new data policy that balances data protection and privacy with the need to fuel AI development.46 Closely related, AI development may increase the imperative for strict security standards. As discussed later in this report, AI algorithms are vulnerable to bias, theft, and manipulation, particularly if the training data set is not adequately curated or protected. During a February 2018 conference with defense industry CEOs, then-Deputy Defense Secretary Patrick Shanahan advocated for higher cybersecurity standards in the commercial sector, stating, “[W]e want the bar to be so high that it becomes a condition of doing business.”47 Some leading commercial LAWS, see CRS Report R44466, Lethal Autonomous Weapon Systems: Issues for Congress, by Nathan J. Lucas. 43 Ana Swanson, “Trump Blocks China-Backed Bid to Buy U.S. Chip Maker,” The New York Times, September 13, 2017, https://www.nytimes.com/2017/09/13/business/trump-lattice-semiconductor-china.html. 44 Paul Scharre and Dean Cheng, Testimony to Subcommittee on Emerging Threats and Capabilities, Hearing on China’s Pursuit of Emerging Technologies. For more information on CFIUS, see CRS Report RL33388, The Committee on Foreign Investment in the United States (CFIUS), by James K. Jackson. 45 The specific technologies that qualify as “emerging and foundational technologies” are to be identified by an interagency process led by the Department of Commerce. See P.L. 115-232, Title XVII, §1702(c). For more information on FIRRMA, see CRS In Focus IF10952, CFIUS Reform: Foreign Investment National Security Reviews, by James K. Jackson and Cathleen D. Cimino-Isaacs. Some entities, including the National Security Commission on Artificial Intelligence, have argued that the U.S. government should consider alternative approaches to AI technology protection, such as “heavier scrutiny of the potential end use and end user of specific items,” that could potentially reduce the burden on U.S. corporations. See National Security Commission on Artificial Intelligence, Interim Report, November 2019, https://drive.google.com/file/d/153OrxnuGEjsUvlxWsFYauslwNeCEkvUb/view. 46 Alexander Velez-Green and Paul Scharre, “The United States Can Be a World Leader in AI. Here’s How.,” The National Interest, November 2, 2017, https://nationalinterest.org/feature/the-united-states-can-be-world-leader-ai- heres-how-22921. 47 Marcus Weisgerber, “Pentagon Warns CEOs: Protect Your Data or Lose Our Contracts,” Defense One, February 6, 2018, http://www.defenseone.com/business/2018/02/pentagon-warns-ceos-protect-your-data-or-lose-our-contracts/ Congressional Research Service 8
Artificial Intelligence and National Security technology companies have issued similar calls for increased scrutiny, with Microsoft president Brad Smith arguing that a lack of regulation in this area could lead to “a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success.”48 Finally, commercial companies have long cited the potential loss of intellectual property rights as a key impediment to partnering with DOD. In recognition of this issue, Section 813 of the FY2016 NDAA established a “government-industry advisory panel” to provide recommendations on technical data rights and intellectual property reform.49 The panel’s report, released in November 2018, offers a number of recommendations, including increased training in intellectual property rights for acquisitions professionals and a pilot program for intellectual property valuation in the procurement process.50 AI Applications for Defense DOD is considering a number of diverse applications for AI. Currently, AI R&D is being left to the discretion of research organizations in the individual services, as well as to DARPA and the Intelligence Advanced Research Projects Agency (IARPA). However, DOD components are required to coordinate with the JAIC regarding any planned AI initiatives costing more than $15 million annually.51 In addition, the JAIC has been tasked with overseeing the National Mission Initiatives (NMI), projects that leverage AI to address pressing operational challenges.52 The JAIC began work on its first two NMIs—predictive maintenance and humanitarian assistance and disaster relief—in 2019. According to JAIC acting director Nand Mulchandani, the JAIC is currently focused on joint warfighting and, in May 2020, was awarded an $800 million contract to Booz Allen Hamilton to “bring AI to the battlefield.”53 AI is being incorporated into a number of other intelligence, surveillance, and reconnaissance applications, as well as in logistics, cyberspace operations, information operations, command and control, semiautonomous and autonomous vehicles, and lethal autonomous weapon systems. 145779/?oref=d-river. For more on cybersecurity legislation, see CRS Report R42114, Federal Laws Relating to Cybersecurity: Overview of Major Issues, Current Laws, and Proposed Legislation, by Eric A. Fischer. 48 Brad Smith, “Facial recognition: It’s time for action,” Microsoft, December 6, 2018, https://blogs.microsoft.com/on- the-issues/2018/12/06/facial-recognition-its-time-for-action/?mod=article_inline. 49 P.L. 114-92, Section 2, Division A, Title VIII, §813. 50 2018 Report, Government-Industry Advisory Panel on Technical Data Rights, November 21, 2018, p. 5, https://sbtc.org/wp-content/uploads/2018/11/Final-Report_ExSum_TensionPapers_11132018.pdf. 51 This coordination threshold will be reviewed each year and adjusted upwards, as conditions warrant. Patrick Shanahan, Deputy Secretary of Defense, Memorandum, “Establishment of the Joint Artificial Intelligence Center,” June 27, 2018, https://admin.govexec.com/media/ establishment_of_the_joint_artificial_intelligence_center_osd008412-18_r.... pdf. 52 Ibid. 53 Other mission initiatives include warfighter health, business process transformation, threat reduction and protection, joint logistics, and joint information warfare. Jackson Barnett, “The vast majority of JAIC’s money is going toward warfighting,” Fedscoop, July 8, 2020, https://www.fedscoop.com/jaic-military-ai-money-war-warfighting-mission- initative/. Congressional Research Service 9
Artificial Intelligence and National Security Intelligence, Surveillance, and Reconnaissance AI is expected to be particularly useful in intelligence due to the large data sets available for analysis.54 For example, Project Maven is intended to incorporate computer vision and machine learning algorithms into intelligence collection cells that would comb through footage from uninhabited aerial vehicles and automatically identify hostile activity for targeting. In this capacity, AI is intended to automate the work of human analysts who currently spend hours sifting through drone footage for actionable information, potentially freeing analysts to make more efficient and timely decisions based on the data.55 The intelligence community also has a number of publicly acknowledged AI research projects in progress. The Central Intelligence Agency alone has around 140 projects in development that leverage AI in some capacity to accomplish tasks such as image recognition and predictive analytics.56 IARPA is sponsoring several AI research projects intended to produce other analytic tools within the next four to five years. Some examples include developing algorithms for multilingual speech recognition and translation in noisy environments, geo-locating images without the associated metadata, fusing 2-D images to create 3-D models, and building tools to infer a building’s function based on pattern-of-life analysis.57 Logistics AI may have future utility in the field of military logistics. The Air Force, for example, is beginning to use AI for predictive aircraft maintenance. Instead of making repairs when an aircraft breaks or in accordance with standardized fleet-wide maintenance schedules, the Air Force is testing an AI-enabled approach that tailors maintenance schedules to the needs of individual aircraft. This approach, currently used by the F-35’s Autonomic Logistics Information System, extracts real-time sensor data embedded in the aircraft’s engines and other onboard systems and feeds the data into a predictive algorithm to determine when technicians need to inspect the aircraft or replace parts.58 Similarly, the Army’s Logistics Support Activity (LOGSA) has contracted IBM’s Watson (the same AI software that defeated two Jeopardy champions) to develop tailored maintenance schedules for the Stryker fleet based on information pulled from the 17 sensors installed on each vehicle. In September 2017, LOGSA began a second project that will use Watson to analyze shipping flows for repair parts distribution, attempting to determine the most time- and cost- efficient means to deliver supplies. This task is currently done by human analysts, who have saved the Army around $100 million a year by analyzing just 10% of shipping requests; with Watson, the Army will have the ability to analyze 100% of shipping requests, potentially generating even greater cost savings in a shorter period of time.59 54 CRS discussions with Dr. Richard Linderman, October 24, 2017. 55 Corrigan, “Three-Star General Wants AI in Every New Weapon System.” 56 Patrick Tucker, “What the CIA’s Tech Director Wants from AI,” Defense One, September 6, 2017, http://www.defenseone.com/technology/2017/09/cia-technology-director-artificial-intelligence/140801/. 57 CRS discussions with Dr. Jason Matheny, IARPA Director, October 10, 2017, and https://www.iarpa.gov/index.php/ research-programs. 58 Marcus Weisgerber, “Defense Firms to Air Force: Want Your Planes’ Data? Pay Up,” Defense One, September 19, 2017, http://www.defenseone.com/technology/2017/09/military-planes-predictive-maintenance-technology/141133/. 59 Adam Stone, “Army Logistics Integrating New AI, Cloud Capabilities,” September 7, 2017, https://www.c4isrnet.com/home/2017/09/07/army-logistics-integrating-new-ai-cloud-capabilities/. Congressional Research Service 10
Artificial Intelligence and National Security Cyberspace Operations AI is likely to be a key technology in advancing military cyber operations. In his 2016 testimony before the Senate Armed Services Committee, Commander of U.S. Cyber Command Admiral Michael Rogers stated that relying on human intelligence alone in cyberspace is “a losing strategy.”60 He later clarified this point, stating, “If you can’t get some level of AI or machine learning with the volume of activity you’re trying to understand when you’re defending networks ... you are always behind the power curve.”61 Conventional cybersecurity tools look for historical matches to known malicious code, so hackers only have to modify small portions of that code to circumvent the defense. AI-enabled tools, on the other hand, can be trained to detect anomalies in broader patterns of network activity, thus presenting a more comprehensive and dynamic barrier to attack.62 DARPA’s 2016 Cyber Grand Challenge demonstrated the potential power of AI-enabled cyber tools. The competition challenged participants to develop AI algorithms that could autonomously “detect, evaluate, and patch software vulnerabilities before [competing teams] have a chance to exploit them”—all within a matter of seconds, rather than the usual months.63 The challenge demonstrated not only the potential speed of AI-enabled cyber tools but also the potential ability of a singular algorithm to play offense and defense simultaneously. These capabilities could provide a distinct advantage in future cyber operations. Information Operations and “Deep Fakes”64 AI is enabling increasingly realistic photo, audio, and video forgeries, or “deep fakes,” that adversaries could deploy as part of their information operations. Indeed, deep fake technology could be used against the United States and U.S. allies to generate false news reports, influence public discourse, erode public trust, and attempt to blackmail diplomats.65 Although most previous deep fakes have been detectable by experts, the sophistication of the technology is progressing to the point that it may soon be capable of fooling forensic analysis tools.66 In order to combat deep fake technologies, DARPA has launched the Media Forensics (MediFor) project, which seeks to “automatically detect manipulations, provide detailed information about how these manipulations were performed, and reason about the overall integrity of visual 60 Testimony of Michael Rogers, Senate Armed Services Committee, Hearing to Receive Testimony on Encryption and Cyber Matters, September 13, 2016, https://www.armed-services.senate.gov/imo/media/doc/16-68_09-13-16.pdf. 61 Amaani Lyle, “National Security Experts Examine Intelligence Challenges at Summit,” September 9, 2016, https://www.defense.gov/News/Article/Article/938941/national-security-experts-examine-intelligence-challenges-at- summit/. 62 Scott Rosenberg, “Firewalls Don’t Stop Hackers, AI Might,” Wired, August 27, 2017, https://www.wired.com/story/ firewalls-dont-stop-hackers-ai-might/. 63 “’Mayhem’ Declared Preliminary Winner of Historic Cyber Grand Challenge,” August 4, 2016, https://www.darpa.mil/news-events/2016-08-04. 64 For a more detailed discussion of information operations, see CRS Report R45142, Information Warfare: Issues for Congress, by Catherine A. Theohary. For a more detailed discussion of deep fakes, see CRS In Focus IF11333, Deep Fakes and National Security, by Kelley M. Sayler and Laurie A. Harris. 65 Kyle Rempfer, “Ever heard of ‘deep fake’ technology? The phony audio and video tech could be used to blackmail US troops,” Military Times, July 19, 2018, https://www.militarytimes.com/news/your-air-force/2018/07/19/ever-heard- of-deep-fake-technology-the-phony-audio-and-video-tech-could-be-used-to-blackmail-us-troops/. 66 Allen and Chan, p. 29. Congressional Research Service 11
Artificial Intelligence and National Security media.”67 MediFor has developed some initial tools for identifying AI-produced forgeries, but as one analyst has noted, “a key problem … is that machine-learning systems can be trained to outmaneuver forensics tools.”68 For this reason, DARPA plans to host follow-on contests to ensure that forensic tools keep pace with deep fake technologies.69 Artificial intelligence could also be used to create full “digital patterns-of-life,” in which an individual’s digital “footprint” is “merged and matched with purchase histories, credit reports, professional resumes, and subscriptions” to create a comprehensive behavioral profile of servicemembers, suspected intelligence officers, government officials, or private citizens.70 As in the case of deep fakes, this information could, in turn, be used for targeted influence operations or blackmail. Command and Control The U.S. military is seeking to exploit AI’s analytic potential in the area of command and control. DOD is developing various systems in support of its concept of Joint All Domain Command and Control (JADC2), which aims to centralize planning and execution of air-, space-, cyberspace-, sea-, and land-based operations.71 In the immediate future, AI may be used to fuse data from sensors in all of these domains to create a single source of information, also known as a “common operating picture,” for decisionmakers.72 Currently, information available to decisionmakers comes in diverse formats from multiple platforms, often with redundancies or unresolved discrepancies. An AI-enabled common operating picture would theoretically combine this information into one display, providing a comprehensive picture of friendly and enemy forces, and automatically resolving variances from input data. Such a system could eventually enable “any sensor to provide data to any shooter from any service, ally, or partner … to achieve effects against any target.”73 The services have a number of related programs that are designed to demonstrate the capabilities needed to execute JADC2, including the Army’s Project Convergence and the Air Force’s Advanced Battle Management System.74 Similarly, DARPA’s Mosaic Warfare program seeks to leverage AI to network systems and sensors, prioritize incoming sensor data, and autonomously determine the optimal composition of forces. 75 67 “Media Forensics (MediFor),” DARPA, https://www.darpa.mil/program/media-forensics. 68 Will Knight, “The Defense Department has produced the first tools for catching deepfakes,” MIT Technology Review, August 7, 2018, https://www.technologyreview.com/s/611726/the-defense-department-has-produced-the-first- tools-for-catching-deepfakes/. 69 Ibid. 70 Clint Watts, “Artificial intelligence is transforming social media. Can American democracy survive?,” Washington Post, September 5, 2018, https://www.washingtonpost.com/news/democracy-post/wp/2018/09/05/artificial- intelligence-is-transforming-social-media-can-american-democracy-survive/?utm_term=.7e7a5ef245db. 71 For more information about JADC2, see CRS In Focus IF11493, Defense Capabilities: Joint All Domain Command and Control, by John R. Hoehn and Nishawn S. Smagh. 72 Colin Clark, “‘Rolling the Marble’: BG Saltzman on Air Force’s Multi-Domain C2 System,” Breaking Defense, August 8, 2017, https://breakingdefense.com/2017/08/rolling-the-marble-bg-saltzman-on-air-forces-multi-domain-c2- system/. 73 Theresa Hitchens, “Air Force Expands 5G As It Transforms to Multi-Domain Ops: Donovan,” Breaking Defense, September 4, 2019, https://breakingdefense.com/2019/09/air-force-expands-5g-as-it-transforms-to-multi-domain-ops- donovan/. 74 Jay Koester, “JADC2 ‘Experiment 2’ provides looking glass into future experimentation,” U.S. Army, April 23, 2020, https://www.army.mil/article/234900/jadc2_experiment_2_provides_looking_glass_into_future_experimentation. 75 “Strategic Technology Office Outlines Vision for ‘Mosaic Warfare,’” DARPA, August 4, 2017, Congressional Research Service 12
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